Dr. I-Chang Yang Profile

Dr. I-Chang Yang

at Agricultural Research Service

SPIE Involvement:

Author

Publications (8)

Proceedings Article | 17 May 2013 Paper

Evaluation of Phalaenopsis flowering quality using near infrared spectroscopy

Suming Chen, Yung-Kun Chuang, Chao-Yin Tsai, Yao-Chien A. Chang, I-Chang Yang, Yung-Huei Chang, Chu-Chun Tai, Jiunn-Yan Hou

Proceedings Volume 8881, 88810F (2013) https://doi.org/10.1117/12.2030710

KEYWORDS: Near infrared, Glucose, Calibration, Near infrared spectroscopy, Reflectance spectroscopy, Inspection, Agriculture, Reflectivity, Spectroscopy, Statistical analysis

Read Abstract +

Proceedings Article | 5 May 2012 Paper

Development of a single-channel, three-view imaging system with classification model for defect and damage assessment of freefalling cereal grains

I-Chang Yang, Stephen Delwiche, Y. Martin Lo

Proceedings Volume 8369, 83690E (2012) https://doi.org/10.1117/12.921419

KEYWORDS: Imaging systems, Inspection, Cameras, Image classification, Image processing, Feature extraction, Mirrors, Classification systems, MATLAB, Affine motion model

Read Abstract +

Currently, inspection of wheat in the United States for grade and class is performed by human visual analysis. This is a time consuming operation typically taking several minutes for each sample. Digital imaging research has addressed this issue over the past two decades, with success in recognition of differing wheat classes, and distinguishing wheat from non-wheat species. Detection of wheat kernel defects, either by damage or disease, has been a greater challenge. A study has been undertaken that uses high-speed black and white imaging at 10-bit photometric resolution to detect damaged kernels one kernel at a time. The system, composed of hardware (camera, lighting, power supplies, and data acquisition card), software (LabVIEW and MATLAB), and analytical (MATLAB and SAS) components, is designed to a) capture images of free-falling kernels at opposing angles through the use of optical grade mirrors, b) parameterize the images and, c) perform classification. The system operates with a 1/30,000 second exposure time though with restrictions on image transfer rate (60 Hz) and image processing routines for feature extraction (currently conducted offline). Fifty samples of hard red and white wheat subjected to weather related damage during plant development were used in this study. Parametric (linear discriminant analysis) and non-parametric (k-nearest neighbor) classification models were tested to determine the image features that best foster recognition of the damage conditions of mold, sprout, and black tip. The morphological features used in classification included area, projected volume, perimeter, elliptical eccentricity, and major and minor axis lengths. Textural features from calculated gray level co-occurrence matrices (including contrast, correlation, energy, and homogeneity), are also under consideration though not reported herein. So far, our results indicate that with as few as three image parameters, classification (damaged vs. sound) levels approach 85 to 90 percent accuracy. Information learned from this study is intended to lead to the streamlining of feature extraction in image-based high speed sorting.

Proceedings Article | 5 May 2012 Paper

Integration of independent component analysis with near infrared spectroscopy for evaluation of rice freshness

Yung-Kun Chuang, Suming Chen, Stephen Delwiche, Y. Martin Lo, Chao-Yin Tsai, I-Chang Yang, Yi-Ping Hu

Proceedings Volume 8369, 83690X (2012) https://doi.org/10.1117/12.921309

KEYWORDS: Independent component analysis, Calibration, Near infrared, Near infrared spectroscopy, Chemical analysis, Agriculture, Spectroscopy, Nondestructive evaluation, Spectral calibration, Inspection

Read Abstract +

Proceedings Article | 28 April 2009 Paper

Hyperspectral imaging for detection of black tip damage in wheat kernels

Stephen Delwiche, I-Chang Yang, Moon Kim

Proceedings Volume 7315, 73150K (2009) https://doi.org/10.1117/12.818791

KEYWORDS: Hyperspectral imaging, Luminescence, Image processing, Inspection, Reflectivity, Electron multiplying charge coupled devices, Image classification, Imaging systems, Software development, Cameras

Read Abstract +

SPIE Journal Paper | 1 February 2009

Enhancement of Fusarium head blight detection in free-falling wheat kernels using a bichromatic pulsed LED design

I-Chang Yang, Stephen Delwiche, Suming Chen, Y. Martin Lo

OE, Vol. 48, Issue 02, 023602, (February 2009) https://doi.org/10.1117/12.10.1117/1.3081092

KEYWORDS: Light emitting diodes, Head, Inspection, Optical engineering, Green light emitting diodes, Reflectivity, Analytical research, Sensors, Optical fibers, Visualization

Read Abstract +

Proceedings Article | 12 October 2007 Paper

Evaluation of nitrogen content in cabbage seedlings using hyper-spectral images

Suming Chen, Chia-Tseng Chen, Ching-Yin Wang, I-Chang Yang, Shih-Chieh Hsiao

Proceedings Volume 6761, 67610L (2007) https://doi.org/10.1117/12.733079

KEYWORDS: Nitrogen, Calibration, Image segmentation, Reflectivity, Data modeling, Imaging systems, Atmospheric modeling, Absorbance, Hyperspectral systems, Image processing

Read Abstract +

Proceedings Article | 23 October 2006 Paper

Development of multi-functional remote sensing system for greenhouse production

Suming Chen, Hung-Chih Lu, Kuang-Wen Hsieh, Yu-I Huang, Chia-Tseng Chen, I-Chang Yang, Chin-Lun Chang, Guan-Hung Yeh

Proceedings Volume 6381, 638103 (2006) https://doi.org/10.1117/12.686151

KEYWORDS: Remote sensing, Imaging systems, Environmental sensing, Calibration, Image segmentation, Sensing systems, Algorithm development, Image processing, Humidity, Control systems

Read Abstract +

Proceedings Article | 9 November 2005 Paper

Study of deacetylation in chitinous materials using near infrared spectroscopy

Suming Chen, Chih-Cheng Tsai, Richie Chen, I-Chang Yang, Hsien-Yi Hsiao, Chia-Tseng Chen, Ci-Wen Yang

Proceedings Volume 5996, 599611 (2005) https://doi.org/10.1117/12.630535

KEYWORDS: Near infrared, Calibration, Near infrared spectroscopy, Inspection, Absorption, Reflectivity, Mathematical modeling, Thermal modeling, Solid state physics, Spectrophotometry

Read Abstract +

Showing 5 of 8 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years